高校大学生体能训练成绩的ADFM模型预测研究  

Research on Prediction of College Students’ Physical Fitness Training Performance Based on ADFM

作　　者：江山[1] JIANG Shan(Fujian Police College,Fuzhou 350007,China)

机构地区：[1]福建警察学院,福建福州350007

出　　处：《兰州文理学院学报（自然科学版）》2024年第3期105-109,共5页Journal of Lanzhou University of Arts and Science(Natural Sciences)

基　　金：2022年福建省教育厅中青年教师教育科研项目(JRT20220536)。

摘　　要：采用深度神经网络预测算法,基于注意力机制的深度因子分解机模型(attentional deep factorization machine,ADFM)预测了高校大学生的体能训练成绩,采用的预测算法模型包括K近邻分类算法和深度神经网络,探讨了3种因素对模型性能的影响以及激活函数对模型的影响.对比实验证明,深度神经网络在预测高校大学生体能训练成绩方面具有较好的效果,可为提高大学生体能训练水平提供模型和数据支持.This paper predicts the performance of college students' physical training based on deep learning.The prediction algorithm models include K-nearest neighbor classification algorithm,and depth neural network.The experimental design and result analysis discuss the influence of three factors on the performance of the model and the influence of activation function on the model.Through the comparative experimental analysis,it is concluded that the depth neural network has a good effect in predicting the performance of college students' physical training,and can provide model and data support for improving the level of college students' physical training.

关 键 词：ADFM模型 高校学生 体能训练 成绩预测 

分 类 号：G804.49[文化科学—运动人体科学]